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给出了基于节点信息的路网空间拓扑结构的具体描述形式。引入相关性概念,提出了一种基于道路几何信息的自适应模糊决策地图匹配算法。通过待配路段两两之间隶属度值的比较与模糊排序以及测度因子参数的适应性调整,使算法在道路几何分布复杂,且较为密集的区域,仍具有较强的适应能力。对实际跑车数据的仿真处理结果表明,该算法较好地解决了城市交叉路口地图匹配问题。
A detailed description of the topological structure of road network based on node information is given. The concept of correlation is introduced and an adaptive fuzzy decision map matching algorithm based on road geometry information is proposed. Through the comparison of membership values and the fuzzy ranking and the adaptive adjustment of the measure factor parameters, the algorithm still has strong adaptability in the areas with complex and dense road geometry distribution. The simulation results of actual sports car data show that the algorithm can solve the problem of map matching at urban intersections.